A graph database is a type of data structure where one or more graphs are used to model the structural relationships between data objects in a data set. Each of the graphs employs nodes (also known as vertices), edges and attributes (also known as properties) to represent and store the data objects. Generally speaking, the nodes in a given graph represent entity instances such as people, businesses, accounts, or any other item of interest. The edges in the graph represent the connections that exist between pairs of nodes. The attributes in the graph are pertinent data that relates to the nodes. Depending on the particular type of graph (e.g., the particular type of data model) being implemented, the attributes in the graph may also be pertinent data that relates to the edges. It is becoming increasingly popular to use graph databases to model complicated, large data sets in a variety of application domains such as bioinformatics applications, cheminformatics applications, repositories of business process models, social network applications, bibliographic network applications, and knowledge base applications.